Recently, many works have been proposed for mining the relationship between objects in a certain area. In the area of small object detection, tiny objects are difficult to be detected and recognized only by its own features. Context information among instances nearby is used to form a group for the measurement on the relationship between each other [1]}, [2]}. In [1]}, Lim et al. extracted the feature of higher layers to obtain the contextual information from surrounding pixels. Among re-ID methods, context information is often represented as the concept of group, which helps model the relationships between the target person and his/her neighboring persons. In [4]}, unlabelled target instances were leveraged as the contextual guidance for image generation. Besides, group re-ID methods [5]}, [6]}, [7]} explore more on how to incorporate the additional visual context from the neighboring group members to enhance the re-ID performance. In terms of person search, there exist several methods [8]}, [9]}, [10]}, [11]} that explore context information. In [8]}, [10]}, [11]}, group context was used by graph matching. In [15]} and [16]}, context was employed in an implicit way by using memory units in the weakly-supervised setting.
